Elections in 2020: the Role of Data in Politics

That was until big data came to the forefront

What is big data? Simply put, datasets large and complex enough as to overwhelm relational software (such as Excel and SPSS).

The consequences of big data for theory-building

It is hard to exaggerate the consequences of big data analysis for theory-building in political science: it is moving the discipline from being a theory-driven enterprise with emphasis on explaining, to a data-driven one with emphasis on prediction. This is a fundamental change in the nature of the discipline. Theory-driven research postulates that correlation is not causation and no conclusion should be made on the basis of covariation. Data-driven research postulates that correlation is sufficient, and accurate predictive models can be built on top of it.

It is exciting, yes, but there is another side of the coin

Some political scientists are sounding the alarm that the use of big data in political campaigning is increasing polarization in societies. This is because strategists are targeting the most ardent supporters with messages and ads designed to rally these die-hards in the final weeks of the campaign. By doing this, however, candidates are ignoring their more moderate voters and dismissing their opponents, driving the electorate to the fringes.

Data is political

Everything about it. How it is produced, collected, distributed, used, and disposed. These decisions do not take place in a vacuum but in a specific political system in which actors have competing interests. Data is not a natural resource nor is its use inconsequential in politics. Now more than ever the act of observation may change what is being observed. As we endeavour to become more predictive and use data in new and imaginative ways, let us not lose sight of the human element in everything. Data is not itself truth. Data is a material we use to get insights to make sense of a world we believe is governed by some sort of causal ordering.

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